Industry-leading Risk-Based Vulnerability Management software company NopSec announced new, improved machine-learning algorithms to its risk scoring functionality. Dedicated to continuous improvement, NopSec’s new risk scoring system updates will deliver more accurate threat data than ever before.
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With more vulnerabilities being discovered each day, Vulnerability Management teams struggle to cut through the noise. They’re often left spending hours discerning between vulnerabilities that have highly weaponized exploit kits and those that don’t. Risk scoring and prioritization tools help SecOps teams identify the vulnerabilities most at-risk for the company — but these too need to innovate as cyberattackers grow more sophisticated.
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“One of the more frustrating things anyone dealing with data has to manage is false positives,” says Adrienne Juett, Data Scientist at NopSec. “Our new risk scoring algorithm cuts down on these false positives using supervised machine learning.”
NopSec, a world leader in cyber exposure management, uses patented machine learning algorithms to precisely calculate the risk of vulnerability exploitation. This enables Vulnerability Management teams to go beyond standard scanner and CVSS scores to identify and rank the criticality of their vulnerabilities. This new feature update will further help clients to eliminate security vulnerability overload.
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